Certain Brain Data Decoded

WWII Code-Breaking Techniques
Inspire Interpretation of Brain Data

Atlanta, GA -- December 18, 2017 -- Cracking the German Enigma code is considered to be one of the decisive factors that hastened Allied victory in World War II. Now researchers have used similar techniques to crack some of the brain’s mysterious code.

By statistically analyzing clues intercepted through espionage, computer science pioneers in the 1940s were able to work out the rules of the Enigma code, turning a string of gibberish characters into plain language to expose German war communications. And today, a team that included computational neuroscientist Eva Dyer, who recently joined the Georgia Institute of Technology, used cryptographic techniques inspired by Enigma’s decrypting to predict, from brain data alone, which direction subjects will move their arms.

The work by researchers from the University of Pennsylvania, Georgia Tech, and Northwestern University could eventually help decode the neural activity underpinning more complex muscle movements and become useful in prosthetics, or even speech, to aid patients with paralysis.

During the war, the team that cracked Enigma, led by Alan Turing, considered the forebear of modern computer science, analyzed the statistical prevalence of certain letters of the alphabet to understand how they were distributed in messages like points on a map. That allowed the code breakers to eventually decipher whole words reliably.

In a similar manner, the neurological research team has now mapped the statistical distribution of more prevalent and less prevalent activities in populations of motor neurons to arrive at the specific hand movements driven by that neural activity.

The research team was led by University of Pennsylvania professor Konrad Kording, and Eva Dyer, formerly a postdoctoral researcher in Kording’s lab and now an assistant professor at Georgia Tech. They collaborated with the group of Lee Miller, a professor at Northwestern University. They published their study on December 12, 2017, in the journal Nature Biomedical Engineering.  .

 

Neuron firing pattern

In an experiment conducted in animal models, the researchers took data from more than one hundred neurons associated with arm movement. As the animals reached for a target that appeared at different locations around a central starting point, sensors recorded spikes of neural activity that corresponded with the movement of the subject’s arm.

“Just looking at the raw neural activity on a visual level tells you basically nothing about the movements it corresponds to, so you have to decode it to make the connection,” Dyer said. “We did it by mapping neural patterns to actual arm movements using machine learning techniques inspired by cryptography.”

The statistical prevalence of certain neurons’ firings paired up reliably and repeatedly with actual movements the way that, in the Enigma project, the prevalence of certain code symbols paired up with the frequency of use of specific letters of the alphabet in written language. In the neurological experiment, an algorithm translated the statistical patterns into visual graphic patterns, and eventually, these aligned with the physical hand movements that they aimed to decode.

“The algorithm tries every possible decoder until we get something where the output looks like typical movements,” Kording said. “There are issues scaling this up — it’s a hard computer science problem — but this is a proof-of-concept that cryptanalysis can work in the context of neural activity.

“At this point, the cryptanalysis approach is very new and needs refining, but fundamentally, it’s a good match for this kind of brain decoding,” Dyer said.

Brain decoding does face a fundamental challenge that code-breaking doesn't.

In cryptography, code-breakers have both the encrypted and unencrypted messages, so all they need to do is to figure out which rules turn one into the other. "What we wanted to do in this experiment was to be able to decode the brain from the encrypted message alone,” Kording said.

http://www.rh.gatech.edu/news/600029/wwii-code-breaking-techniques-inspire-interpretation-brain-data